The other day we did something we don’t like to do when talking about flu, we made a prediction. We predicted a bad swine flu season in the fall in the northern hemisphere. The history of flu epidemiology is that making predictions is dangerous. Flu has the ability to make fools out of anyone, regardless of expertise. One commenter in particular disdained the risk we took as being no risk at all. It was perfectly obvious to him (or “anyone paying attention”) that next flu season would be a swine flu horror show. It may well be, and then this commenter will certainly gloat and perhaps have justification for doing so. But since this is a site where we try to add some value to what you can read anywhere (whether it is Fool’s Gold or not, you and history will decide), we thought it might be useful to explain why we think that what looks obvious may not be so obvious.
First, if you make a prediction it’s nice to give some reasoning. The commenter’s reasoning was that “anyone paying attention to what was going on in the southern hemisphere” would see that things were going to hell in a handbasket there, with health care workers “dying in droves.” The evidence for this last is a newspaper article saying 10% of the dead in Argentina were health care workers. When we suggested such reports had yet to be verified, his response was to point to a news report of a nurse in California who had died of the swine flu and ask if we likewise rejected this report. We give these details not for the purpose of arguing against a single commenter but to make a point about data. Not all newspaper reports are equal. It is perfectly possible for a newspaper to give an accurate report about the death of a single person. That is something reporters know how to get accurate information about and we all know such information is often available. But when newspapers start reporting about things that are much more difficult for anyone to get accurate information about it is different. As an epidemiologist I know first hand that it is rarely as simple as counting or accepting reports. If you’ve never investigated an outbreak, you probably wouldn’t be aware that the first step, verify the diagnosis, often has surprising results. I have personally looked into numerous cancer clusters, based on first hand reports from individuals in neighborhoods that “I have brain cancer, my next door neighbor has brain cancer, the lady across the street died of brain cancer, etc.” only to find out that some of the people had other kinds of cancer or didn’t have cancer at all. Even more surprising is that you find out that some people have been diagnosed with cancer but don’t know it or don’t know what kind of cancer. It’s not just true for cancer. If you do a random sample of people and ask them how many have been diagnosed with lupus, for example, you will get a substantial overestimate of the true figure, because many people take a doctor saying “You had a positive lupus test” as meaning they have lupus. On the other hand, if the newspaper gives the number of cases of cancer in a town based on the report of the state’s cancer registry, we are more inclined to take it is reliable data. Not all reports are equal, not even all newspaper reports.

As we saw in Mexico originally and is being repeated in many other countries, some kinds of information on infectious diseases can be very hard to ascertain, too. In the midst of stress, fear and the necessity to make estimates and guesses, it can be difficult to even count the dead from flu, much less ascertain their occupations or whether there is any relation of their occupation and getting the flu (many people identified as nurses and doctors don’t work in health care settings or work in health care settings where they are any more likely to see flu patients than in the grocery store). When I hear a figure in a newspaper that 10% of the dead are health care workers (who by implication got flu in the course of their work), I first ask myself if there is any way that the newspaper — or anyone — is likely to have an accurate fix on that number. It isn’t like the nurse in California. Even in the US, CDC had to do a special study in a very restricted time frame and geographic area to get some information on health care worker cases. Is the number in Argentina truly 10% of the dead? It could be, but I doubt anyone knows at this point. That’s why my reply to the commenter was, “We’ll see” and his misinterpretation was that I was rejecting any newspaper report as false. I wasn’t. As an epidemiologist I know not all data are created equal. Some is more certain than others.

In a similar vein, the commenter pointed to news reports of the collapse of the health care delivery system in the southern hemisphere as it tried to cope with an overwhelming demand. When confronted by other commenters who actually lived in some of those countries that this was a gross exaggeration, the response was this was inconsistent with what he had been reading in the newspapers. This isn’t exactly the same as the numbers issue, but it’s worth commenting on. For one thing, in a very bad flu season (and it appears that Australia and New Zealand are seeing what looks to be a bad season), some health services will indeed be overwhelmed. It happens in the US even without a bad flu season because our health care system is so brittle, inefficient and with no reserve capacity. But it’s also true that flu is notoriously patchy in time and space and what you see in one place is not necessarily what you will see in another. I think a newspaper can, with some accuracy, report conditions in emergency rooms, although there will always be the added element of spin to sell newspapers. But disagreements on how to describe what is happening can be honest and accurate and all parties can be seeing some of the truth, perhaps describing it differently. One thing for sure, however. The disparate ways the situation is being seen by observers, whether through reading it in the newspapers up north or experiencing it on the ground down south certainly doesn’t constitute a situation that could be called obvious to “anyone paying attention.” Again, it’s a question of having some experience understanding and evaluating the data and when to put weight on it and why.

Presumably the reason for the commenter bringing these things up was the inference that if the southern hemisphere was having a really bad flu season it was a given that we would also have one in the fall. We were not willing to make that leap without having some reasoning behind it. Again, this is a difference between how epidemiologists think and what might seem obvious on its face to a non-epidemiologist. Maybe epidemiologists are too cautious about things like this, but we are scientists and it is our experience that things are often not what they appear to be on the surface. This goes double for influenza. Consider some examples.

Let’s return to the patchiness of influenza. The toll it takes on the population varies from year to year. There are some serious technical difficulties on how this impact is estimated (see our post here), but it is measured in excess mortality, not actual mortality from flu (which is not determinable with current data). There is only an excess when the number of people dying during flu season exceeds a certain threshold (one standard deviation above an estimated average mortality that varies throughout the year). In some years there is no excess at all (like three out of the last four years). Last year there was quite a large excess. Sometimes the excess is extremely large, 70,000 or more. Sometimes it is zero. Over many flu seasons it averages 30,000 – 40,000 (or sometimes higher depending on how the estimate is done), with some of the years being essentially zero excess and others very high. When we talk about “a severe flu season” we are talking about one in which the excess is large. For interpandemic years the bulk of the excess is in the oldest age group, 65 years and older. Some of the variation from year to year seems to be related to seasonal subtype, with H3N2 years worse than H1N1 years, but sometimes H3N2 years can vary substantially, too. In the last couple of decades there is a four fold difference in excess mortality in bad versus not so bad H3N2 years (source for this is the Viboud et al. article, discussed next). We don’t know why this is.

In an interesting article in the journal Vaccine in 2006, Viboud et al. (this team is among the most experienced analysts of historical influenza statistics in the world) drew attention to the unusual influenza season of 1951 (we posted on another paper on this subject in 2006). But they did more than discuss 1951. They compared a measure of virus transmissibility (effective R, like R0), which they estimated for all pandemics and severe interpandemic flu seasons from 1918 to 1970 (they did not use data from “mild” flu seasons because there is no excess mortality to give reliable data). They used the method of Mills, Robins and Lipsitch, first published in 2004 to estimate R0 for the 1918 pandemic.

One of the big surprises was that in terms of mortality, 1951 was as, or even more severe, in England and Wales and Canada than the 1918 pandemic. The epicenter of the 1951 season was Liverpool where transmissibility and mortality of the virus was higher than all three waves of 1918 and also the 1957 pandemic and much higher than the 1968 pandemic. But 1951 had no other hallmarks of a pandemic year. The mortality pattern remained heavily on the elderly and there was no evidence genetic shift or drift. The two previous seasons had been mild or moderate. There was no evidence of antigenic differences to account for this single season outlier. There are no genetic sequences available for the 1951 virus, so we don’t know what made it so transmissible. One explanation is that some effect on viral fitness may have been responsible. An influenza virus has eight genetic segments that work together as a team. It is surmised that some kind of reassortment involving the internal genes might have made a difference in transmissibility and/or virulence. We don’t know. Viboud et al. point to more recent seasons where in some locations the virus seems genetically similar but behaves differently epidemiologically in some locations (but not others). Examples are two severe H3N2 seasons, 1989-90 in the UK (A/England/89 and 1999-2000 in the US (A/Sydney/97). As the authors state, “These observations remain unexplained.” Even more striking was that the same season (1951) was a mild flu season in the US and northern Europe. It appears two different H1N1 flu strains may have been simultaneously circulating with different geographic distributions.

Given this history, perhaps our reluctance to predict, even when it might seem “obvious” to some, is more understandable. Not much about flu is obvious. But we did make a prediction anyway, based more on a hunch than any set of reasons we thought “obvious.” At least we were frank in saying it was a hunch and we gave some detailed reasoning that led up to it. That’s about all we feel comfortable doing at this point.

Comments

Revere,
Perhaps there are a couple other reasons to feel uneasy about this fall, as well. One is uncertainty over the amount of oseltamivir-resistant novel H1N1 that is circulating, and the other is uncertainty over the amount of vaccine-mismatched H3N2 we may see. In both cases, there are just enough data to raise questions, but hardly enough to provide answers. H274Y has been identified overseas in isolates from at least two patients with disease so mild that they would not qualify for sequencing in the US (both patients, by history, appear to have acquired their infections in the US). CDC acknowledges the existence of the vaccine mismatch (and reports that H3N2 is the dominant seasonal virus in the Southern Hemisphere thus far), but collecting and sequencing novel H1N1 isolates has taken priority.

SoCal: The resistance thing depends mainly on what the virus is like otherwise. Almost all H1N1 seasonal virus is resistant and we get by fine as long as the season isn’t terrible. Regarding the H3N2 mismatch possibility, there is shockingly little info being released about this. All I know is that a certain proportion (not specified) of southern hemisphere H3N2 (location and proportion of cases that are H3N2 also not specified) don’t match the Brisbane strain well. That’s not much info to go on and I sure would like more.

A question from the peanut gallery – this was from The Doctor in an ealier thread:

The fact that the novel H1N1 virus does not yet posses the HA 627 polymorphism required for ideal reproduction within the temperature of human upper respiratory tract is something that has impaired its reproduction rate. That it will acquire this PM soon is likely. When it does, then it will be much more fit; meaning its spread among humans will be enhanced.
(My bold, since it is Relevant To My Interests).

Magpie: I believe he was referring to the E627K mutation in PB2 (not HA) which is associated with adaptation of avian viruses to humans in previous examples. Surprisingly, the swine flu H1N1 virus doesn’t have it. It has been surmised that the mutation is related to the different body temp of humans compared to birds and allows the virus to infect host human cells more easily, but since this is a swine virus and doesn’t have it its relevance is unclear. Like a lot of things. The E is a one letter abbreviation for the amino acid glutamic acid, usually found in avian viruses at location 627 in the polymerase gene segment (PB2) while the K is the one letter abbreviation for lysine, the amino acid found at that position in the mutated (or we thought, human adapted) virus. This is one of the many little mysteries we don’t understand about flu.

this is an excellent post and should stimulate some equivalent careful, thoughtful reasoning among the readers. when mexico actually gained the ability to test for the new H1, half of the deaths in the initial outbreak were due to something else than flu.

I have personally looked into numerous cancer clusters, based on first hand reports from individuals in neighborhoods that “I have brain cancer, my next door neighbor has brain cancer, the lady across the street died of brain cancer, etc.” only to find out that some of the people had other kinds of cancer or didn’t have cancer at all. Even more surprising is that you find out that some people have been diagnosed with cancer but don’t know it or don’t know what kind of cancer.

This sounds plausible but strange.

How can you think you have cancer and not have it, or have it somewhere else?

How can you be diagnosed with cancer and not know it?

Old people can get confused or forgetful so they have an excuse. Must be more than that going on here.

Totally surprised that you’ve done this is an understatement revere and yet a reluctant welcome and a finally.
Was just getting to the point where the “we don’t know” heard so often from you was being accepted.

raven: Doctors don’t always tell patients they have cancer or patients don’t always hear it. Or a euphemism (“a new growth”) is used. Or it is called by a scientific name (you have a neoplasm), etc., Believe me. It’s true. Also the details about where the cancer came from (the primary site) are often hazy. Metastases to the brain become brain cancers. Similarly reports from neighbors or second hand that so and so has cancer or had cancer, etc., are frequently false or inaccurate. And there are benign tumors that are not cancers because they are not malignant, or the doctor is trying to rule out cancer or mentioned cancer, etc., etc. I’ve seen it all.

This particular comment in the original essay really jumped out at me:”There are some serious technical difficulties on how this impact is estimated (see our post here), but it is measured in excess mortality, not actual mortality from flu (which is not determinable with current data)” Let me raise a hypothetical, then, IF a particular year in the US were one with several very severe winter storms, that is, events with icy roads, deep snow, power failures, supply delivery failures… AND then a serious number of somewhat older citizens died due to falls, lack of heat, traffic accidents on black ice, and so on, would those numbers automatically contribute to any “excess mortality” for that particular flu season?

DryHeat: It depends. If the excess is measured in pneumonia and influenza deaths, probably not. If in all causes, the other deaths would contribute to the noise and make it harder to get the flu signal out. It also depends on how the regression is done (i.e., what other variables are being controlled for). So there is no easy answer. If you go to the link about determining excess deaths, you will see some of the formidable difficulties.

revere, since I’m “the commentator” you refer to in your blog, why not use my handle? I don’t want to change it to “The Commentator formerly known as Monotreme”. 😉

The suggestion that I will gloat at some point is unfair (as were similar suggestions from Magpie that I enjoy predicting catastrophe). A more accurate depiction of my emotional state would be disappointment in those who are supposed to protect public health along with a grim determination to their job for them.

It is true that flu seasons differ from year to year, but when has a pandemic suddenly ceased after a few months? Scientists at the CDC and elsewhere have indicated that the Southern Hemisphere is worth watching to get clues as to what will happen in the fall. This is not a controversial position to take, although you seem to imply that it is.

You put great stock in the testimony from a couple of your commentators, but little in press reports? Why are some anonymous claims more believable than press reports? There are many “first hand” accounts in the media of overwhelmed ERs and ICUs, most recently in India. Unless you have some reason to believe that these many reports are false, I’m not sure why you dismiss them.

I agree that it would be better to have hard data to analyze. However, the CDC is doing its very best to hide this information from the public. They haven’t released their seroprevalence studies. They no longer provide information on the total number of cases. They now hide which states have how many deaths. Any NYC, from whence the Director hails, now hides all new deaths from the general public. You have defended at least some these actions in previous blogs. So, you applaud the CDC for hiding data while criticising me for using the only data I can get my hands on, press reports. Again, this seems a bit unfair.

However, I am glad that my comments spurred you to write this blog. fwiw, my interaction there spurred me to write this one .

Mono: revere, since I’m “the commentator” you refer to in your blog, why not use my handle? I don’t want to change it to “The Commentator formerly known as Monotreme”. 😉

I didn’t name you for two reasons. The first is that I don’t usually single out commenters on the front page. I don’t think it’s fair to them. The equally important reason was that I wasn’t really talking about you. I was just using your comments to make some points about how epidemiologists think.

The suggestion that I will gloat at some point is unfair (as were similar suggestions from Magpie that I enjoy predicting catastrophe). A more accurate depiction of my emotional state would be disappointment in those who are supposed to protect public health along with a grim determination to their job for them.

Granted, it was a bit snarky. But you have also been more than unfair in your comments (see below). I think you would concede that I am “paying attention” to what is going on. Your tone was not at all fair or gracious. I don’t really care. The internet is a rough and tumble place and I give us good as I get. But you brought it up, so that’s my response.

It is true that flu seasons differ from year to year, but when has a pandemic suddenly ceased after a few months? Scientists at the CDC and elsewhere have indicated that the Southern Hemisphere is worth watching to get clues as to what will happen in the fall. This is not a controversial position to take, although you seem to imply that it is.

We don’t know how often pandemics have ceased because we’ve not been able to follow this before. But I would suggest to you that both the UK/Canadian 1951 strain (which co-circulated with the Scandinavian strain) and the Fort Dix swine flu strain could well be interpreted as aborted pandemics. We don’t have enough information to know that, but it is quite a plausible interpretation. You seem to think we know much more than we do.

You put great stock in the testimony from a couple of your commentators, but little in press reports? Why are some anonymous claims more believable than press reports? There are many “first hand” accounts in the media of overwhelmed ERs and ICUs, most recently in India. Unless you have some reason to believe that these many reports are false, I’m not sure why you dismiss them.

I have no idea what or whom you are talking about. I’ve explained to you the press issue and written about the press here often. It’s true I don’t put much stock in your comments and I am explaining why. I also discussed the ER issue and the newspaper in the post. Read it again.

I agree that it would be better to have hard data to analyze. However, the CDC is doing its very best to hide this information from the public. They haven’t released their seroprevalence studies. They no longer provide information on the total number of cases. They now hide which states have how many deaths. Any NYC, from whence the Director hails, now hides all new deaths from the general public. You have defended at least some these actions in previous blogs. So, you applaud the CDC for hiding data while criticising me for using the only data I can get my hands on, press reports. Again, this seems a bit unfair.

If you want an example of “unfair,” you’ve just provided it. What evidence do you have that CDC is doing its best to hide information from the public? You have none. Just your suspicions and prejudgments, which frankly I find stupid and offensive. You’ve never been in the trenches. I’ll leave it at that.

Mono: That’s all been explained here and by CDC. You don’t understand it. That’s not my problem. They don’t report flu case numbers during the year, either. They can’t because they don’t know them. As for seroprevalence studies, which ones do you claim they are hiding and why? I did not “primarily” choose ad hominem attacks as my response. I said I found your accusations against hard working public servants at CDC stupid and offensive. That’s a statement of fact. I said you’ve never been in the trenches. That’s a statement of fact. All of it was point by point and you can call it not serious if you wish. I have a different interpretation as to why you don’t respond.

Revere, pardon the intrusion into this “stoush” between yourself and Mono re: “differing public health roleplay realities and expectations” — that’s how I’m interpreting the language being used by you both (Revere, “Idiot” + Mono “Invasion of the Body Snatcher pod person sell out”).

Anyway… I’m on a bit of a learning curve here. I don’t even know if America has a federal agency collating disease numbers similar to Australia’s Department of Health and Ageing (see below)!?! Who is collecting the national data!?! Where are the statistical charts that are based on official government numbers? Who is keeping track?

Excerpt: Nick, “As I’ve discussed before, the Department of Health and Ageing have a “notifiable diseases report generator” that will give you a table of disease notifications, which is then easy to graph. So, I’ve run this generator for influenza notifications and got some interesting stats.

The first graph shows the number of influenza notifications in Australia for the years 2001 to 2008 (8 years all up), by month… Note that these are notifications for all types of flu (not just swine flu, which wasn’t around in its present form anyway)…

[The final] graph tells the story well enough as to just how bad this season is compared to a normal season. The only caveat I would add to this is that we have clearly undertaken a lot more testing for flu in Australia this season than in a normal season. So some of the marked increase in notifications has to be due to an increased testing effect. Just how much – I don’t know…”

Jon: The US also has swine flu as a “notifiable disease.” It depends on doctors notifying the state health dept. There are two problems. Most don’t do it. They don’t know if their patient has swine flu or not because there is no office test for it. The same is true for regular flu (which is not notifiable but it wouldn’t matter). No one is hiding the information. It just isn’t available. It is available only in principle (like weighing the moon on a balance is available “in principle”). You’d have to do swabs on everyone in the country and then do PCR on each of them. Instead we rely on sampling via surveillance systems. So Australia doesn’t know either. Epidemiologists understand what these numbers mean and they are used as rough indicators for planning purposes in health departments but they have little to do with how many people are infected with influenza.

Mono: I understand your explanations, and the CDC’s, I just don’t buy them.

You think it totally normal for NYC to suddenly stop reporting their deaths. Well, OK. I don’t.

You are entitled to believe every explanation the CDC provides. Just don’t assume that those who don’t are stupid or necessarily wrong.

btw, I’m not attacking all “the hard working public servants at the CDC”, just some of them. You know, like you used to do. Before someone stuck a pod next to your bed.

On one side we have 50 state health departments (who pushed hard for CDC to do this earlier), CDC, WHO and every infectious disease epidemiologist I am aware of who has voiced an opinion about this; on the other side we have Monotreme, who just doesn’t buy it.

So let me ask you, exactly what is it that you don’t buy? In the early phases of this outbreak we counted cases. It was providing some information because it hadn’t established general transmission in the community. Once that happened, though, the numbers that were being released bore little relationship to reality. No one had any accurate information about how many cases there were. It was no longer possible to count them and any counts that were released would be misleading. CDC, far from hiding the true extent, made headlines by saying they believed the true number was anywhere between ten and a hundred times the counts, although how much more wasn’t possible to say. When the counts were only a few thousand, CDC was saying there might be 100,000 or more. That’s hiding the true extent?

The states wanted to stop counting because they were being overwhelmed by the work load of doing something of marginal utility. When I said you’d never been in the trenches it was not a general comment but a specific one. You have not the least idea what the situation on the ground is for understaffed, overworked and resource poor health departments that you want to provide you with information that wouldn’t even be accurate. It’s not as if they have nothing else to do. They have decisions to make every day about how to allocate scarce resources to indigent mothers and children, HIV positive people, restaurants, nursing homes, etc., etc. They aren’t sitting around pecking at their keyboard thinking, “I wonder what Monotreme wants to know today.” CDC went to an “all hands” status to deal with this. This means they have diverted people from other duties to answer the many urgent questions that need answering: setting up studies, collecting data, analyzing results, giving technical help to state and local health, running off to the southern hemisphere (and being separated from their family for extended periods), working long hours. They have to use resources as efficiently as possible and even then they aren’t sufficient. They’ve decided — for very good reasons — that your interests aren’t at the top of their list. Yes, I’ve been critical of CDC’s leadership in the past. But pardon me if I think I might have more of a basis for judgment about this than you do. I’ve dealt with CDC in one way or another for many decades. I have some basis for my judgments. You can argue with them, but they aren’t uninformed or crazy conspiracy theories. You are solidly in tinfoil hat country.

Finally, maybe you see something CDC, all state health departments, WHO and most every infectious disease epidemiologist I am aware of who has stated an opinion about the case counting issue. So tell the rest of us. How, exactly, do you propose to count all the cases of swine flu? I’m not talking prevalent cases of ever infected. Those estimates will likely be made with some kind of seroprevalence data, although exactly how to do this is not completely clear or straightforward. But that’s not counting cases. That’s estimating them with a study. How about incident cases so you can construct an epidemic curve? How are you going to count all the new cases in a time period of infected people? All of them. Please tell me. If you just want to estimate them, CDC is doing that with the different components of their surveillance system. You can get the data every Friday on their website. All the deaths? Since you’ve never tried to count deaths before (I doubt you’ve even seen a real death certificate much less filled one out), I would be most interested as to how you think you are going to do this now that transmission is widespread in the community. Most deaths have no autopsies. Flu can contribute to death in many ways that don’t look like flu. We don’t even know the true cause of death for many cases. But you insist that it be done. How, exactly?

I don’t buy that the public health establishment is primarily motivated by a desire to protect human lives.

Note, I am talking about “management”, not the worker bees. The top dogs in public health are politicians, not scientists. Most of them have never done a single experiment in their lives. Many have never published a single peer-reviewed paper. And almost none have ever competed for grant money that was judged by a peer review committee. Instead, they have made their way up the career ladder by keeping the politicians who appointed them happy, whatever that required. That’s also how they got money for their agencies.

I don’t doubt that county public health departments are under-resourced. But whose fault is that? Not the worker bees, I agree. But how about the State and Federal public health officials? Where have they been? Why haven’t they advocated for more funding? The CDC could have played an important role in setting standards for what is expected in terms of data about illness and death. Instead, they’ve chosen passivity as a strategy.

An influenza pandemic is clearly one of the biggest impact challenges that public health could face. Everyone knew that. Yet, the CDC did nothing to prepare for testing large numbers of samples. You keep going on and on about how much work it is to do PCR. So let me tell you something, you don’t know what you are talking about. There are now automated systems that allow a single technician to process 384 samples at a time. The CDC had more than enough money to buy a room full of these machines and get them ready to go. They should also have been talking to the States about their ability to process large numbers of samples. Some large states, like California, New York, Texas and Florida, could easily have set these machines up ahead of time. Smaller states without the technical expertise could have sent their samples to the CDC. This is not hugely expensive nor labor intensive. If the CDC was run by actual scientists, they would know this.

We need to continue to test for several reasons. Let me list them:

1. To identify people who need Tamiflu. We do not have enough to give to everyone with ILI. But if we wait until more than 48 hours, it may be too late.

2. To identify the true CFR in different age groups. The CDC has repeatedly claimed that this virus is “mild” without presenting any hard data. Telephone surveys during allergy season don’t count.

3. To identify changes in the ability of the virus to infect people.

4. To identify changes in the ability of the virus to cause disease.

5. To identify strains that need to be sequenced, ie, flu strains for which the primers fail. This is a sign that a new variant may have emerged.

Counting deaths is not hard, now. Unless you know something I don’t. Everyone who dies of a respiratory disease should be tested for the new H1N1. As I pointed out above, that would not be hard to do.

As regards conspiracy theories, members of the Obama administration have repeatedly discussed the economic effects of different interventions like school closures. And, what a coincidence, Director Frieden has decided we don’t need to close the schools. He says we know how to “manage” cases in the schools. What a load of bullshit.

Perhaps you have missed this, but someone at the CDC is uploading Director’s briefings to Cryptome. Some of the information from these briefings is eventually made public, but much of it is not. The CFR by age information hasn’t been made public. How come?

Are there any prospective plans to figure a way to count the flu dead rather than all? Take samples from inconclusive corpses and test them all at end of year or month or whenever?
Are there nations (Canada, UK) estimating these tallies more accurate than CDC or same style methodology?

Regardless of how much “trouble” it is track flu cases world wide, there are several really compelling reasons to do so and the fact that the effort isn’t even being made is unbelievable to me. First reason: do it so we are no longer stumbling around in the dark as if it is still 1918, or 1957, clueless and unable to predict a thing. In the computer age this seems inexcusable.

How hard would it be, actually, to take samples randomly from 1 out of 10 patients presenting with ILI at clinics, ERs and hospitals, and send these off to the CDC (or whatever its equivalent in your country of choice.) Out of the 15 minutes or so allowed per patient visit, which includes taking their weight,temp, bp, O2 stats etc, taking this sample of blood or sputum would add what, an additional minute or two? Omit the unnecessary weight taking if you need to save some time.

Packing a box of these samples each day for pick up by Fed ex takes another what, 10 or 15 minutes? That’s not an overwhelm for most hospitals and clinics. At the CDC, hire a staff of lab workers who do nothing but analyze these samples and input the results into a central computer, which then graphs trends and makes predictions, issues alerts and so on. I’m sure there are plenty of recent grads looking for work who could do this.

Point is, without the ongoing data we have nothing, no clue to either predict the course of this pandemic, nor to plan for the next. Without data we never become proactive, never get to apply science to the situation. Which means the virus wins while we watch and wring our hands helpless as ever. May as well be a horn blowing rabbi in an airplane, for all the good “science” is doing us right now.

Mary: It’s not that it’s too much trouble. It’s that it’s impossible. Most cases of flu aren’t even seen by a practitioner, much less diagnosed. And there is another kind of cost besides money. Health dept. labs have many other things to do besides flu testing, whose value is marginal. Nor is it true that without counting every case we have nothing. We have an ongoing surveillance system to give us valuable information. We do have quite a bit of data. Would we like more? Of course. Let’s put some money into surveillance. It will cost money but that’s the way it is.

maryinhawaii, the claims about “too much work” are a smokescreen to hide data that would affect the economy. The CDC has lots of information that they have chosen not tell the public. Like, for example, that the CFR for 25 – 49 years olds is 1.5% and for 50 – 64 years old is 3.33%. An insider at the CDC has apparently been releasing internal CDC documents. I notice that revere doesn’t seem to want to talk about this, but you can read one of the leaked reports here:

Revere, how did my suggesting that they test 1 out of 10 cases that actually show up at a hospital or clinic with ILI ( ie ARE “seen by a practioner”) become “counting every case”? Random sampling is just that: it gives a statistical base from which a broader picture can be extrapolated of the flu’s infectivity, virulence and cfr, and any changes in same.

And the public from which this information is being withheld, either by commission or omission, does not mean just the semi uninvolved general public who might or might not know what the data means and what to do about it. The GPs, the HCWs in the trenches, the public school administrators and School nurses are not being told anything either. These are the ones with whom two way communication on outbreaks are vital to the health of the nation. As to whether local or state government authorities are being kept informed, who knows. If they are, it’s being kept from the rest of us.

Also, I don’t think one should minimize the importance of the role flublogia plays in trying to track, predict and keep the world informed about the flu…which they can’t do without up to date and accurate information from the sources receiving it.

Mono: Oh for God’s sake. Do you have the slightest idea how to interpret epi data? Anyone with even a tiny bit of experience knows there is no way that the CFR for 65+ is 5%. In mid July no one knew (and they still don’t know) what the denominator is. Do you even know what a CFR is? This wasn’t leaked or secret data. It was data so preliminary that its release would lead to the cockamamie interpretations you just gave it without being compensatorily informative. It is not confidential, just FOUO because it was a working document. You just illustrated why they don’t put it up for the general public.Epi data isn’t just counting things, whatever you may think.

mary: The ILI sampling is being done by the NREVSS system. So, as I said, it’s surveillance and it’s being done. I don’t minimize floblogia’s role. I just know what it is, having been a part of it since before it was flublogia. It’s quite valuable for H5N1 tracking but not for H1N1 tracking. Since it’s officially being said there are likely millions of cases, how is that info being withheld? What info do you want that isn’t already produced by the many part surveillance system and why do you want it and how are you going to get it?

revere, I assume that the CDC knows what CFR means. I did not label the figure CFR, the CDC did. Also, I didn’t “interpret” it, I reported it. If the CDC has better data now, where is it? If you have evidence that “there is no way that the 65+ CFR is 5%”, where is it? Just asserting things based on your experience is not science, it’s arrogance.

Your post indicates why more and more people are coming to distrust people who claim to speak on behalf on public health. Arrogant assertions replace data and actual data is suppressed because the public are viewed as too stupid to process it correctly.

I find it ironic that you criticise Religion every Sunday. Arrogance, paternalism, dogma, suppression of embarrassing facts, punishment of those who challenge its authority: Organised religion has got nothing on the public health estabalishment.

As regards the missing denominator, is the CDC less able to calculate this than investigators in 1918? We ought to be able to compare apples with apples in terms of CFR. We don’t need perfect information to do this.

Mono: The 1918 CFR is very uncertain for the same reasons. It has been the subject of discussion amongst epidemiologists. But you and I can agree on one thing. You don’t interpret. You just report. Selectively, and without any other thought than if it agrees with your paranoid fantasies. If your only purpose in commenting here is to irritate me, don’t bother. But you have your own blog. Use it in good health. Anyone interested in your reporting can go there.

revere, I had hoped that you would rethink your assumptions, as you did when I challenged your assertion that H5N1 could not possibly be as lethal as it was. It took you a while, but eventually you came around to my point of view on that subject.

I don’t know if you are a different “revere” or if the old revere is no longer able to tolerate dissent. But whatever, I get the message.

Mono is very likely right about one thing… Its not about the counting… Its more about the reasons they are NOT counting. They say its redundant now to do this and expensive. It is.

On the other hand we are being told its mild with dead people lying about in various places. Dont count them in Mexico. Dont call it severe, and damned sure dont close those airports..Shit, its bad, oh so bad for the economy.

But there are bigger things. Then there is that nagging 2 full combat brigades question. You know the ones that only have 2 battalions of medical staff and one field hospital unit assigned to it to be set up on existing federal installations. A battalion is about 80 people in medical staffing, a field hospital is about 250. So 400 people are going to save us from the swine flu that they arent counting? What are the other 15,000 combat troops, combat air and ground support people for pray tell? How does a Blackhawk help with swiney? Do tell.

Why are they setting up on federal installations where only the federal military justice system is in place. And why is the military setting up for this when there is no federalization order of any kind in the first place? Now thats some good questions.

Forget the numbers guys. The total toe tags and whether Mary in Hawaii just happens to notice that little Johnny and Little Janie aint in their seats after a couple of days gone missing are going to be the biggest questions.

We also have to watch whether some jerk from ACORN with a thermal imager has the right to send you to a camp. Probably would up those chances by 100% if you were one of the “mob” or the”Nazi’s” that Pelosi was calling people. It would be redundant to mention Republicans in that… they’ll just round them up automatically.